Multiple forms of activity-dependent intrinsic plasticity in layer V cortical neurones in vivo

SanPy: Software for the analysis and visualization of whole-cell current-clamp recordings

The analysis of action potentials and other membrane voltage fluctuations provides a powerful approach for interrogating the function of excitable cells. However, a major bottleneck in the interpretation of this critical data is the lack of intuitive, agreed-upon software tools for its analysis. Here, we present SanPy, an open-source and freely available software package for the analysis and exploration of whole-cell current-clamp recordings written in Python. SanPy provides a robust computational engine with an application programming interface. Using this, we have developed a cross-platform desktop application with a graphical user interface that does not require programming. SanPy is designed to extract common parameters from action potentials, including threshold time and voltage, peak, half-width, and interval statistics. In addition, several cardiac parameters are measured, including the early diastolic duration and rate. SanPy is built to be fully extensible by providing a plugin architecture for the addition of new file loaders, analysis, and visualizations. A key feature of SanPy is its focus on quality control and data exploration. In the desktop interface, all plots of the data and analysis are linked, allowing simultaneous data visualization from different dimensions with the goal of obtaining ground-truth analysis. We provide documentation for all aspects of SanPy, including several use cases and examples. To test SanPy, we performed analysis on current-clamp recordings from heart and brain cells. Taken together, SanPy is a powerful tool for whole-cell current-clamp analysis and lays the foundation for future extension by the scientific community.

Neuroprotective Effects of Ferrostatin and Necrostatin Against Entorhinal Amyloidopathy-Induced Electrophysiological Alterations Mediated by voltage-gated Ca2+ Channels in the Dentate Gyrus Granular Cells

Alzheimer's disease (AD) is a progressive neurodegenerative disease that is the main form of dementia. Abnormal deposition of amyloid-beta (Aβ) peptides in neurons and synapses cause neuronal loss and cognitive deficits. We have previously reported that ferroptosis and necroptosis were implicated in Aβ25-35 neurotoxicity, and their specific inhibitors had attenuating effects on cognitive impairment induced by Aβ25-35 neurotoxicity. Here, we aimed to examine the impact of ferroptosis and necroptosis inhibition following the Aβ25-35 neurotoxicity on the neuronal excitability of dentate gyrus (DG) and the possible involvement of voltage-gated Ca2+ channels in their effects. After inducing Aβ25-35 neurotoxicity, electrophysiological alterations in the intrinsic properties and excitability were recorded by the whole-cell patch-clamp under current-clamp condition. Voltage-clamp recordings were also performed to shed light on the involvement of calcium channel currents. Aβ25-35 neurotoxicity induced a considerable reduction in input resistance (Rin), accompanied by a profoundly decreased excitability and a reduction in the amplitude of voltage-gated calcium channel currents in the DG granule cells. However, three days of administration of either ferrostatin-1 (Fer-1), a ferroptosis inhibitor, or Necrostatin-1 (Nec-1), a necroptosis inhibitor, in the entorhinal cortex could almost preserve the normal excitability and the Ca2+ currents. In conclusion, these findings suggest that ferroptosis and necroptosis involvement in EC amyloidopathy could be a potential candidate to prevent the suppressive effect of Aβ on the Ca2+ channel current and neuronal function, which might take place in neurons during the development of AD.

SanPy: A whole-cell electrophysiology analysis pipeline

The analysis of action potentials and other membrane voltage fluctuations provide a powerful approach for interrogating the function of excitable cells. Yet, a major bottleneck in the interpretation of this critical data is the lack of intuitive, agreed upon software tools for its analysis. Here, we present SanPy, a Python-based open-source and freely available software pipeline for the analysis and exploration of whole-cell current-clamp recordings. SanPy provides a robust computational engine with an application programming interface. Using this, we have developed a cross-platform graphical user interface that does not require programming. SanPy is designed to extract common parameters from action potentials including threshold time and voltage, peak, half-width, and interval statistics. In addition, several cardiac parameters are measured including the early diastolic duration and rate. SanPy is built to be fully extensible by providing a plugin architecture for the addition of new file loaders, analysis, and visualizations. A key feature of SanPy is its focus on quality control and data exploration. In the desktop interface, all plots of the data and analysis are linked allowing simultaneous data visualization from different dimensions with the goal of obtaining ground truth analysis. We provide documentation for all aspects of SanPy including several use cases and examples. To test SanPy, we have performed analysis on current-clamp recordings from heart and brain cells. Taken together, SanPy is a powerful tool for whole-cell current-clamp analysis and lays the foundation for future extension by the scientific community.

Intrinsic threshold plasticity: cholinergic activation and role in the neuronal recognition of incomplete input patterns

Activity-dependent changes in membrane excitability are observed in neurons across brain areas and represent a cell-autonomous form of plasticity (intrinsic plasticity; IP) that in itself does not involve alterations in synaptic strength (synaptic plasticity; SP). Non-homeostatic IP may play an essential role in learning, e.g. by changing the action potential threshold near the soma. A computational problem, however, arises from the implication that such amplification does not discriminate between synaptic inputs and therefore may reduce the resolution of input representation. Here, we investigate consequences of IP for the performance of an artificial neural network in (a) the discrimination of unknown input patterns and (b) the recognition of known/learned patterns. While negative changes in threshold potentials in the output layer indeed reduce its ability to discriminate patterns, they benefit the recognition of known but incompletely presented patterns. An analysis of thresholds and IP-induced threshold changes in published sets of physiological data obtained from whole-cell patch-clamp recordings from L2/3 pyramidal neurons in (a) the primary visual cortex (V1) of awake macaques and (b) the primary somatosensory cortex (S1) of mice in vitro, respectively, reveals a difference between resting and threshold potentials of ∼15 mV for V1 and ∼25 mV for S1, and a total plasticity range of ∼10 mV (S1). The most efficient activity pattern to lower threshold is paired cholinergic and electric activation. Our findings show that threshold reduction promotes a shift in neural coding strategies from accurate faithful representation to interpretative assignment of input patterns to learned object categories. KEY POINTS: Intrinsic plasticity may change the action potential threshold near the soma of neurons (threshold plasticity), thus altering the input-output function for all synaptic inputs 'upstream' of the plasticity location. A potential problem arising from this shared amplification is that it may reduce the ability to discriminate between different input patterns. Here, we assess the performance of an artificial neural network in the discrimination of unknown input patterns as well as the recognition of known patterns subsequent to changes in the spike threshold. We observe that negative changes in threshold potentials do reduce discrimination performance, but at the same time improve performance in an object recognition task, in particular when patterns are incompletely presented. Analysis of whole-cell patch-clamp recordings from pyramidal neurons in the primary somatosensory cortex (S1) of mice reveals that negative threshold changes preferentially result from electric stimulation of neurons paired with the activation of muscarinic acetylcholine receptors.

Visual Cortical Plasticity: Molecular Mechanisms as Revealed by Induction Paradigms in Rodents

Assessing the molecular mechanism of synaptic plasticity in the cortex is vital for identifying potential targets in conditions marked by defective plasticity. In plasticity research, the visual cortex represents a target model for intense investigation, partly due to the availability of different in vivo plasticity-induction protocols. Here, we review two major protocols: ocular-dominance (OD) and cross-modal (CM) plasticity in rodents, highlighting the molecular signaling pathways involved. Each plasticity paradigm has also revealed the contribution of different populations of inhibitory and excitatory neurons at different time points. Since defective synaptic plasticity is common to various neurodevelopmental disorders, the potentially disrupted molecular and circuit alterations are discussed. Finally, new plasticity paradigms are presented, based on recent evidence. Stimulus-selective response potentiation (SRP) is one of the paradigms addressed. These options may provide answers to unsolved neurodevelopmental questions and offer tools to repair plasticity defects.

Reversibility and developmental neuropathology of linear nevus sebaceous syndrome caused by dysregulation of the RAS pathway

Linear nevus sebaceous syndrome (LNSS) is a neurocutaneous disorder caused by somatic gain-of-function mutations in KRAS or HRAS. LNSS brains have neurodevelopmental defects, including cerebral defects and epilepsy; however, its pathological mechanism and potentials for treatment are largely unclear. We show that introduction of KRAS^G12V in the developing mouse cortex results in subcortical nodular heterotopia and enhanced excitability, recapitulating major pathological manifestations of LNSS. Moreover, we show that decreased firing frequency of inhibitory neurons without KRAS^G12V expression leads to disrupted excitation and inhibition balance. Transcriptional profiling after destabilization domain-mediated clearance of KRAS^G12V in human neural progenitors and differentiating neurons identifies reversible functional networks underlying LNSS. Neurons expressing KRAS^G12V show molecular changes associated with delayed neuronal maturation, most of which are restored by KRAS^G12V clearance. These findings provide insights into the molecular networks underlying the reversibility of some of the neuropathologies observed in LNSS caused by dysregulation of the RAS pathway.

Mild membrane depolarization in neurons induces immediate early gene transcription and acutely subdues responses to successive stimulus

Immediate early genes (IEGs) are transcribed in response to neuronal activity from sensory stimulation during multiple adaptive processes in the brain. The transcriptional profile of IEGs is indicative of the duration of neuronal activity, but its sensitivity to the strength of depolarization remains unknown. Also unknown is whether activity history of graded potential changes influence future neuronal activity. In this work with dissociated rat cortical neurons, we found that mild depolarization—mediated by elevated extracellular potassium (K⁺)—induces a wide array of rapid IEGs and transiently depresses transcriptional and signaling responses to a successive stimulus. This latter effect was independent of de novo transcription, translation, and signaling via calcineurin or mitogen-activated protein kinase. Furthermore, as measured by multiple electrode arrays and calcium imaging, mild depolarization acutely subdues subsequent spontaneous and bicuculline-evoked activity via calcium- and N-methyl-d-aspartate receptor–dependent mechanisms. Collectively, this work suggests that a recent history of graded potential changes acutely depress neuronal intrinsic properties and subsequent responses. Such effects may have several potential downstream implications, including reducing signal-to-noise ratio during synaptic plasticity processes.

Intrinsic excitability mechanisms of neuronal ensemble formation

Neuronal ensembles are coactive groups of cortical neurons, found in spontaneous and evoked activity, that can mediate perception and behavior. To understand the mechanisms that lead to the formation of ensembles, we co-activated layer 2/3 pyramidal neurons in brain slices from mouse visual cortex, in animals of both sexes, replicating in vitro an optogenetic protocol to generate ensembles in vivo. Using whole-cell and perforated patch-clamp pair recordings we found that, after optogenetic or electrical stimulation, coactivated neurons increased their correlated activity, a hallmark of ensemble formation. Coactivated neurons showed small biphasic changes in presynaptic plasticity, with an initial depression followed by a potentiation after a recovery period. Optogenetic and electrical stimulation also induced significant increases in frequency and amplitude of spontaneous EPSPs, even after single-cell stimulation. In addition, we observed unexpected strong and persistent increases in neuronal excitability after stimulation, with increases in membrane resistance and reductions in spike threshold. A pharmacological agent that blocks changes in membrane resistance reverted this effect. These significant increases in excitability can explain the observed biphasic synaptic plasticity. We conclude that cell-intrinsic changes in excitability are involved in the formation of neuronal ensembles. We propose an ‘iceberg’ model, by which increased neuronal excitability makes subthreshold connections suprathreshold, enhancing the effect of already existing synapses, and generating a new neuronal ensemble.

In the brain, groups of neurons that are activated together – also known as neuronal ensembles – are the basic units that underpin perception and behavior. Yet, exactly how these coactive circuits are established remains under investigation.

In 1949, Canadian psychologist Donald Hebb proposed that, when brains learn something new, the neurons which are activated together connect to form ensembles, and their connections become stronger each time this specific piece of knowledge is recalled. This idea that ‘neurons that fire together, wire together’ can explain how memories are acquired and recalled, by strengthening their wiring.

However, recent studies have questioned whether strengthening connections is the only mechanism by which neural ensembles can be created. Changes in the excitability of neurons (how easily they are to fire and become activated) may also play a role. In other words, ensembles could emerge because certain neurons become more excitable and fire more readily.

To solve this conundrum, Alejandre-García et al. examined both hypotheses in the same system. Neurons in slices of the mouse visual cortex were stimulated electrically or optically, via a technique that controls neural activity with light. The activity of individual neurons and their connections was then measured with electrodes.

Spontaneous activity among connected neurons increased after stimulation, indicative of the formation of neuronal ensembles. Connected neurons also showed small changes in the strength of their connections, which first decreased and then rebounded after an initial recovery period.

Intriguingly, cells also showed unexpected strong and persistent increases in neuronal excitability after stimulation, such that neurons fired more readily to the same stimulus. In other words, neurons maintained a cellular memory of having been stimulated. The authors conclude that ensembles form because connected neurons become more excitable, which in turn, may strengthen connections of the circuit at a later stage.

These results provide fresh insights about the neural circuits underpinning learning and memory. In time, the findings could also help to understand disorders such as Alzheimer’s disease and schizophrenia, which are characterised by memory impairments and disordered thinking.

Basic mechanisms of plasticity and learning

The last century was characterized by a significant scientific effort aimed at unveiling the neurobiological basis of learning and memory. Thanks to the characterization of the mechanisms regulating the long-term changes of neuronal synaptic connections, it was possible to understand how specific neural networks shape themselves during the acquisition of memory traces or complex motor tasks. In this chapter, we will summarize the mechanisms underlying the main forms of synaptic plasticity taking advantage of the studies performed in the hippocampus and in the nucleus striatum, key brain structures that play a crucial role in cognition. Moreover, we will discuss how the molecular pathways involved in the induction of physiologic synaptic long-term changes could be disrupted during neurodegenerative and neuroinflammatory disorders, highlighting the translational relevance of this intriguing research field.

Resurgent Na+ currents promote ultrafast spiking in projection neurons that drive fine motor control

The underlying mechanisms that promote precise spiking in upper motor neurons controlling fine motor skills are not well understood. Here we report that projection neurons in the adult zebra finch song nucleus RA display robust high-frequency firing, ultra-narrow spike waveforms, superfast Na⁺ current inactivation kinetics, and large resurgent Na⁺ currents (I_NaR). These properties of songbird pallial motor neurons closely resemble those of specialized large pyramidal neurons in mammalian primary motor cortex. They emerge during the early phases of song development in males, but not females, coinciding with a complete switch of Na+ channel subunit expression from Navβ3 to Navβ4. Dynamic clamping and dialysis of Navβ4's C-terminal peptide into juvenile RA neurons provide evidence that Navβ4, and its associated I_NaR, promote neuronal excitability. We thus propose that I_NaR modulates the excitability of upper motor neurons that are required for the execution of fine motor skills.

Reduced Dopamine Signaling Impacts Pyramidal Neuron Excitability in Mouse Motor Cortex

Dopaminergic modulation is essential for the control of voluntary movement; however, the role of dopamine in regulating the neural excitability of the primary motor cortex (M1) is not well understood. Here, we investigated two modes by which dopamine influences the input/output function of M1 neurons. To test the direct regulation of M1 neurons by dopamine, we performed whole-cell recordings of excitatory neurons and measured excitability before and after local, acute dopamine receptor blockade. We then determined whether chronic depletion of dopaminergic input to the entire motor circuit, via a mouse model of Parkinson's disease, was sufficient to shift M1 neuron excitability. We show that D1 receptor (D1R) and D2R antagonism altered subthreshold and suprathreshold properties of M1 pyramidal neurons in a layer-specific fashion. The effects of D1R antagonism were primarily driven by changes to intrinsic properties, while the excitability shifts following D2R antagonism relied on synaptic transmission. In contrast, chronic depletion of dopamine to the motor circuit with 6-hydroxydopamine induced layer-specific synaptic transmission-dependent shifts in M1 neuron excitability that only partially overlapped with the effects of acute D1R antagonism. These results suggest that while acute and chronic changes in dopamine modulate the input/output function of M1 neurons, the mechanisms engaged are distinct depending on the duration and origin of the manipulation. Our study highlights the broad influence of dopamine on M1 excitability by demonstrating the consequences of local and global dopamine depletion on neuronal input/output function.

Intrinsic plasticity and birdsong learning

Although information processing and storage in the brain is thought to be primarily orchestrated by synaptic plasticity, other neural mechanisms such as intrinsic plasticity are available. While a number of recent studies have described the plasticity of intrinsic excitability in several types of neurons, the significance of non-synaptic mechanisms in memory and learning remains elusive. After reviewing plasticity of intrinsic excitation in relation to learning and homeostatic mechanisms, we focus on the intrinsic properties of a class of basal-ganglia projecting song system neurons in zebra finch, how these related to each bird's unique learned song, how these properties change over development, and how they are maintained dynamically to rapidly change in response to auditory feedback perturbations. We place these results in the broader theme of learning and changes in intrinsic properties, emphasizing the computational implications of this form of plasticity, which are distinct from synaptic plasticity. The results suggest that exploring reciprocal interactions between intrinsic and network properties will be a fruitful avenue for understanding mechanisms of birdsong learning.

Neuronal spike-rate adaptation supports working memory in language processing

Language processing involves the ability to store and integrate pieces of information in working memory over short periods of time. According to the dominant view, information is maintained through sustained, elevated neural activity. Other work has argued that short-term synaptic facilitation can serve as a substrate of memory. Here we propose an account where memory is supported by intrinsic plasticity that downregulates neuronal firing rates. Single neuron responses are dependent on experience, and we show through simulations that these adaptive changes in excitability provide memory on timescales ranging from milliseconds to seconds. On this account, spiking activity writes information into coupled dynamic variables that control adaptation and move at slower timescales than the membrane potential. From these variables, information is continuously read back into the active membrane state for processing. This neuronal memory mechanism does not rely on persistent activity, excitatory feedback, or synaptic plasticity for storage. Instead, information is maintained in adaptive conductances that reduce firing rates and can be accessed directly without cued retrieval. Memory span is systematically related to both the time constant of adaptation and baseline levels of neuronal excitability. Interference effects within memory arise when adaptation is long lasting. We demonstrate that this mechanism is sensitive to context and serial order which makes it suitable for temporal integration in sequence processing within the language domain. We also show that it enables the binding of linguistic features over time within dynamic memory registers. This work provides a step toward a computational neurobiology of language.

Muscarinic Modulation of SK2-Type K+ Channels Promotes Intrinsic Plasticity in L2/3 Pyramidal Neurons of the Mouse Primary Somatosensory Cortex

Muscarinic acetylcholine receptors (mAChRs) inhibit small-conductance calcium-activated K+ channels (SK channels) and enhance synaptic weight via this mechanism. SK channels are also involved in activity-dependent plasticity of membrane excitability ("intrinsic plasticity"). Here, we investigate whether mAChR activation can drive SK channel-dependent intrinsic plasticity in L2/3 cortical pyramidal neurons. Using whole-cell patch-clamp recordings from these neurons in slices prepared from mouse primary somatosensory cortex (S1), we find that brief bath application of the mAChR agonist oxotremorine-m (oxo-m) causes long-term enhancement of excitability in wild-type mice that is not observed in mice deficient of SK channels of the SK2 isoform. Similarly, repeated injection of depolarizing current pulses into the soma triggers intrinsic plasticity that is absent from SK2 null mice. Intrinsic plasticity lowers spike frequency adaptation and attenuation of spike firing upon prolonged activation, consistent with SK channel modulation. Depolarization-induced plasticity is prevented by bath application of the protein kinase A (PKA) inhibitor H89, and the casein kinase 2 (CK2) inhibitor TBB, respectively. These findings point toward a recruitment of two known signaling pathways in SK2 regulation: SK channel trafficking (PKA) and reduction of the calcium sensitivity (CK2). Using mice with an inactivation of CaMKII (T305D mice), we show that intrinsic plasticity does not require CaMKII. Finally, we demonstrate that repeated injection of depolarizing pulses in the presence of oxo-m causes intrinsic plasticity that surpasses the plasticity amplitude reached by either manipulation alone. Our findings show that muscarinic activation enhances membrane excitability in L2/3 pyramidal neurons via a downregulation of SK2 channels.

Kv1.1 contributes to a rapid homeostatic plasticity of intrinsic excitability in CA1 pyramidal neurons in vivo

In area CA1 of the hippocampus, the selection of place cells to represent a new environment is biased towards neurons with higher excitability. However, different environments are represented by orthogonal cell ensembles, suggesting that regulatory mechanisms exist. Activity-dependent plasticity of intrinsic excitability, as observed in vitro, is an attractive candidate. Here, using whole-cell patch-clamp recordings of CA1 pyramidal neurons in anesthetized rats, we have examined how inducing theta-bursts of action potentials affects their intrinsic excitability over time. We observed a long-lasting, homeostatic depression of intrinsic excitability which commenced within minutes, and, in contrast to in vitro observations, was not mediated by dendritic I_h. Instead, it was attenuated by the Kv1.1 channel blocker dendrotoxin K, suggesting an axonal origin. Analysis of place cells’ out-of-field firing in mice navigating in virtual reality further revealed an experience-dependent reduction consistent with decreased excitability. We propose that this mechanism could reduce memory interference.

Conditioning by subthreshold synaptic input changes the intrinsic firing pattern of CA3 hippocampal neurons

Unlike synaptic strength, intrinsic excitability is assumed to be a stable property of neurons. For example, learning of somatic conductances is generally not incorporated into computational models, and the discharge pattern of neurons in response to test stimuli is frequently used as a basis for phenotypic classification. However, it is increasingly evident that signal processing properties of neurons are more generally plastic on the timescale of minutes. Here we demonstrate that the intrinsic firing patterns of CA3 neurons of the rat hippocampus in vitro undergo rapid long-term plasticity in response to a few minutes of only subthreshold synaptic conditioning. This plasticity on the spike timing could also be induced by intrasomatic injection of subthreshold depolarizing pulses and was blocked by kinase inhibitors, indicating that discharge dynamics are modulated locally. Cluster analysis of firing patterns before and after conditioning revealed systematic transitions toward adapting and intrinsic burst behaviors, irrespective of the patterns initially exhibited by the cells. We used a conductance-based model to decide appropriate pharmacological blockade and found that the observed transitions are likely due to recruitment of low-voltage calcium and Kv7 potassium conductances. We conclude that CA3 neurons adapt their conductance profile to the subthreshold activity of their input, so that their intrinsic firing pattern is not a static signature, but rather a reflection of their history of subthreshold activity. In this way, recurrent output from CA3 neurons may collectively shape the temporal dynamics of their embedding circuits.NEW & NOTEWORTHY Although firing patterns are widely conserved across the animal phyla, it is still a mystery why nerve cells present such diversity of discharge dynamics upon somatic step currents. Adding a new timing dimension to the intrinsic plasticity literature, here we show that CA3 neurons rapidly adapt through the space of known firing patterns in response to the subthreshold signals that they receive from their embedding circuit, potentially adjusting their network processing to the temporal statistics of their circuit.

The contribution of ion channels in input-output plasticity

Persistent changes that occur in brain circuits are classically thought to be mediated by long-term modifications in synaptic efficacy. Yet, many studies have shown that voltage-gated ion channels located at the input and output side of the neurons are also the subject to persistent modifications. These channels are thus responsible for intrinsic plasticity that is expressed in many different neuronal types including glutamatergic principal neurons and GABAergic interneurons. As for synaptic plasticity, activation of synaptic glutamate receptors initiate persistent modification in neuronal excitability. We review here how synaptic input can be efficiently altered by activity-dependent modulation of ion channels that control EPSP amplification, spike threshold or resting membrane potential. We discuss the nature of the learning rules shared by intrinsic and synaptic plasticity, the mechanisms of ion channel regulation and the impact of intrinsic plasticity on induction of synaptic modifications.

Reorganization of Recurrent Layer 5 Corticospinal Networks Following Adult Motor Training

Recurrent synaptic connections between neighboring neurons are a key feature of mammalian cortex, accounting for the vast majority of cortical inputs. Although computational models indicate that reorganization of recurrent connectivity is a primary driver of experience-dependent cortical tuning, the true biological features of recurrent network plasticity are not well identified. Indeed, whether rewiring of connections between cortical neurons occurs during behavioral training, as is widely predicted, remains unknown. Here, we probe M1 recurrent circuits following motor training in adult male rats and find robust synaptic reorganization among functionally related layer 5 neurons, resulting in a 2.5-fold increase in recurrent connection probability. This reorganization is specific to the neuronal subpopulation most relevant for executing the trained motor skill, and behavioral performance was impaired following targeted molecular inhibition of this subpopulation. In contrast, recurrent connectivity is unaffected among neighboring layer 5 neurons largely unrelated to the trained behavior. Training-related corticospinal cells also express increased excitability following training. These findings establish the presence of selective modifications in recurrent cortical networks in adulthood following training.SIGNIFICANCE STATEMENT Recurrent synaptic connections between neighboring neurons are characteristic of cortical architecture, and modifications to these circuits are thought to underlie in part learning in the adult brain. We now show that there are robust changes in recurrent connections in the rat motor cortex upon training on a novel motor task. Motor training results in a 2.5-fold increase in recurrent connectivity, but only within the neuronal subpopulation most relevant for executing the new motor behavior; recurrent connectivity is unaffected among adjoining neurons that do not execute the trained behavior. These findings demonstrate selective reorganization of recurrent synaptic connections in the adult neocortex following novel motor experience, and illuminate fundamental properties of cortical function and plasticity.

Fast and flexible sequence induction in spiking neural networks via rapid excitability changes

Cognitive flexibility likely depends on modulation of the dynamics underlying how biological neural networks process information. While dynamics can be reshaped by gradually modifying connectivity, less is known about mechanisms operating on faster timescales. A compelling entrypoint to this problem is the observation that exploratory behaviors can rapidly cause selective hippocampal sequences to 'replay' during rest. Using a spiking network model, we asked whether simplified replay could arise from three biological components: fixed recurrent connectivity; stochastic 'gating' inputs; and rapid gating input scaling via long-term potentiation of intrinsic excitability (LTP-IE). Indeed, these enabled both forward and reverse replay of recent sensorimotor-evoked sequences, despite unchanged recurrent weights. LTP-IE 'tags' specific neurons with increased spiking probability under gating input, and ordering is reconstructed from recurrent connectivity. We further show how LTP-IE can implement temporary stimulus-response mappings. This elucidates a novel combination of mechanisms that might play a role in rapid cognitive flexibility.

Tune it in: mechanisms and computational significance of neuron-autonomous plasticity

The activity of a neural network is a result of synaptic signals that convey the communication between neurons and neuron-based intrinsic currents that determine the neuron’s input-output transfer function. Ample studies have demonstrated that cell-based excitability, and in particular intrinsic excitability, is modulated by learning and that these modifications play a key role in learning-related behavioral changes. The field of cell-based plasticity is largely growing, and it entails numerous experimental findings that demonstrate a large diversity of currents that are affected by learning. The diverse effect of learning on the neuron’s excitability emphasizes the need for a framework under which cell-based plasticity can be categorized to enable the assessment of the computational roles of the intrinsic modifications. We divide the domain of cell-based plasticity into three main categories, where the first category entails the currents that mediate the passive properties and single-spike generation, the second category entails the currents that mediate spike frequency adaptation, and the third category entails a novel learning-induced mechanism where all excitatory and inhibitory synapses double their strength. Curiously, this elementary division enables a natural categorization of the computational roles of these learning-induced plasticities. The computational roles are diverse and include modification of the neuronal mode of action, such as bursting, prolonged, and fast responsive; attention-like effect where the signal detection is improved; transfer of the network into an active state; biasing the competition for memory allocation; and transforming an environmental cue into a dominant cue and enabling a quicker formation of new memories.

Toward a Neurocentric View of Learning

Synaptic plasticity (e.g., long-term potentiation [LTP]) is considered the cellular correlate of learning. Recent optogenetic studies on memory engram formation assign a critical role in learning to suprathreshold activation of neurons and their integration into active engrams ("engram cells"). Here we review evidence that ensemble integration may result from LTP but also from cell-autonomous changes in membrane excitability. We propose that synaptic plasticity determines synaptic connectivity maps, whereas intrinsic plasticity-possibly separated in time-amplifies neuronal responsiveness and acutely drives engram integration. Our proposal marks a move away from an exclusively synaptocentric toward a non-exclusive, neurocentric view of learning.

Logarithmic distributions prove that intrinsic learning is Hebbian

In this paper, we present data for the lognormal distributions of spike rates, synaptic weights and intrinsic excitability (gain) for neurons in various brain areas, such as auditory or visual cortex, hippocampus, cerebellum, striatum, midbrain nuclei. We find a remarkable consistency of heavy-tailed, specifically lognormal, distributions for rates, weights and gains in all brain areas examined. The difference between strongly recurrent and feed-forward connectivity (cortex vs. striatum and cerebellum), neurotransmitter (GABA (striatum) or glutamate (cortex)) or the level of activation (low in cortex, high in Purkinje cells and midbrain nuclei) turns out to be irrelevant for this feature. Logarithmic scale distribution of weights and gains appears to be a general, functional property in all cases analyzed. We then created a generic neural model to investigate adaptive learning rules that create and maintain lognormal distributions. We conclusively demonstrate that not only weights, but also intrinsic gains, need to have strong Hebbian learning in order to produce and maintain the experimentally attested distributions. This provides a solution to the long-standing question about the type of plasticity exhibited by intrinsic excitability.

Logarithmic distributions prove that intrinsic learning is Hebbian

In this paper, we document lognormal distributions for spike rates, synaptic weights and intrinsic excitability (gain) for neurons in various brain areas, such as auditory or visual cortex, hippocampus, cerebellum, striatum, midbrain nuclei. We find a remarkable consistency of heavy-tailed, specifically lognormal, distributions for rates, weights and gains in all brain areas. The difference between strongly recurrent and feed-forward connectivity (cortex vs. striatum and cerebellum), neurotransmitter (GABA (striatum) or glutamate (cortex)) or the level of activation (low in cortex, high in Purkinje cells and midbrain nuclei) turns out to be irrelevant for this feature. Logarithmic scale distribution of weights and gains appears as a functional property that is present everywhere.  Secondly, we created a generic neural model to show that Hebbian learning will create and maintain lognormal distributions. We could prove with the model that not only weights, but also intrinsic gains, need to have strong Hebbian learning in order to produce and maintain the experimentally attested distributions. This settles a long-standing question about the type of plasticity exhibited by intrinsic excitability.

Motor Training Promotes Both Synaptic and Intrinsic Plasticity of Layer II/III Pyramidal Neurons in the Primary Motor Cortex

Motor skill training induces structural plasticity at dendritic spines in the primary motor cortex (M1). To further analyze both synaptic and intrinsic plasticity in the layer II/III area of M1, we subjected rats to a rotor rod test and then prepared acute brain slices. Motor skill consistently improved within 2 days of training. Voltage clamp analysis showed significantly higher α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid/N-methyl-d-aspartate (AMPA/NMDA) ratios and miniature EPSC amplitudes in 1-day trained rats compared with untrained rats, suggesting increased postsynaptic AMPA receptors in the early phase of motor learning. Compared with untrained controls, 2-days trained rats showed significantly higher miniature EPSC amplitude and frequency. Paired-pulse analysis further demonstrated lower rates in 2-days trained rats, suggesting increased presynaptic glutamate release during the late phase of learning. One-day trained rats showed decreased miniature IPSC frequency and increased paired-pulse analysis of evoked IPSC, suggesting a transient decrease in presynaptic γ-aminobutyric acid (GABA) release. Moreover, current clamp analysis revealed lower resting membrane potential, higher spike threshold, and deeper afterhyperpolarization in 1-day trained rats—while 2-days trained rats showed higher membrane potential, suggesting dynamic changes in intrinsic properties. Our present results indicate dynamic changes in glutamatergic, GABAergic, and intrinsic plasticity in M1 layer II/III neurons after the motor training.

Depdc5 knockout rat: A novel model of mTORopathy

DEP-domain containing 5 (DEPDC5), encoding a repressor of the mechanistic target of rapamycin complex 1 (mTORC1) signaling pathway, has recently emerged as a major gene mutated in familial focal epilepsies and focal cortical dysplasia. Here we established a global knockout rat using TALEN technology to investigate in vivo the impact of Depdc5-deficiency. Homozygous Depdc5(-/-) embryos died from embryonic day 14.5 due to a global growth delay. Constitutive mTORC1 hyperactivation was evidenced in the brains and in cultured fibroblasts of Depdc5(-/-) embryos, as reflected by enhanced phosphorylation of its downstream effectors S6K1 and rpS6. Consistently, prenatal treatment with mTORC1 inhibitor rapamycin rescued the phenotype of Depdc5(-/-) embryos. Heterozygous Depdc5(+/-) rats developed normally and exhibited no spontaneous electroclinical seizures, but had altered cortical neuron excitability and firing patterns. Depdc5(+/-) rats displayed cortical cytomegalic dysmorphic neurons and balloon-like cells strongly expressing phosphorylated rpS6, indicative of mTORC1 upregulation, and not observed after prenatal rapamycin treatment. These neuropathological abnormalities are reminiscent of the hallmark brain pathology of human focal cortical dysplasia. Altogether, Depdc5 knockout rats exhibit multiple features of rodent models of mTORopathies, and thus, stand as a relevant model to study their underlying pathogenic mechanisms.

Excitability and responsiveness of rat barrel cortex neurons in the presence and absence of spontaneous synaptic activity in vivo

The amplitude and temporal dynamics of spontaneous synaptic activity in the cerebral cortex vary as a function of brain states. To directly assess the impact of different ongoing synaptic activities on neocortical function, we performed in vivo intracellular recordings from barrel cortex neurons in rats under two pharmacological conditions generating either oscillatory or tonic synaptic drive. Cortical neurons membrane excitability and firing responses were compared, in the same neurons, before and after complete suppression of background synaptic drive following systemic injection of a high dose of anaesthetic. Compared to the oscillatory state, the tonic pattern resulted in a more depolarized and less fluctuating membrane potential (Vm), a lower input resistance (Rm) and steeper relations of firing frequency versus injected current (F-I). Whatever their temporal dynamics, suppression of background synaptic activities increased mean Vm, without affecting Rm, and induced a rightward shift of F-I curves. Both types of synaptic drive generated a high variability in current-induced firing rate and patterns in cortical neurons, which was much reduced after removal of spontaneous activity. These findings suggest that oscillatory and tonic synaptic patterns differentially facilitate the input-output function of cortical neurons but result in a similar moment-to-moment variability in spike responses to incoming depolarizing inputs.

Activity-dependent neural plasticity from bench to bedside

Much progress has been made in understanding how behavioral experience and neural activity can modify the structure and function of neural circuits during development and in the adult brain. Studies of physiological and molecular mechanisms underlying activity-dependent plasticity in animal models have suggested potential therapeutic approaches for a wide range of brain disorders in humans. Physiological and electrical stimulations as well as plasticity-modifying molecular agents may facilitate functional recovery by selectively enhancing existing neural circuits or promoting the formation of new functional circuits. Here, we review the advances in basic studies of neural plasticity mechanisms in developing and adult nervous systems and current clinical treatments that harness neural plasticity, and we offer perspectives on future development of plasticity-based therapy.

Bidirectional plasticity of intrinsic excitability controls sensory inputs efficiency in layer 5 barrel cortex neurons in vivo

Responsiveness of cortical neurons to sensory inputs can be altered by experience and learning. While synaptic plasticity is generally proposed as the underlying cellular mechanism, possible contributions of activity-dependent changes in intrinsic excitability remain poorly investigated. Here, we show that periods of rhythmic firing in rat barrel cortex layer 5 pyramidal neurons can trigger a long-lasting increase or decrease in their membrane excitability in vivo. Potentiation of cortical excitability consisted of an increased firing in response to intracellular stimulation and a reduction in threshold current for spike initiation. Conversely, depression of cortical excitability was evidenced by an augmented firing threshold leading to a reduced current-evoked spiking. The direction of plasticity depended on the baseline level of spontaneous firing rate and cell excitability. We also found that changes in intrinsic excitability were accompanied by corresponding modifications in the effectiveness of sensory inputs. Potentiation and depression of cortical neuron excitability resulted, respectively, in an increased or decreased firing probability on whisker-evoked synaptic responses, without modifications in the synaptic strength itself. These data suggest that bidirectional intrinsic plasticity could play an important role in experience-dependent refinement of sensory cortical networks.

Plasticity of motor threshold and motor-evoked potential amplitude--a model of intrinsic and synaptic plasticity in human motor cortex?

BACKGROUND

Neuronal plasticity is the physiological correlate of learning and memory. In animal experiments, synaptic (i.e. long-term potentiation (LTP) and depression (LTD)) and intrinsic plasticity are distinguished. In human motor cortex, cortical plasticity can be demonstrated using transcranial magnetic stimulation (TMS). Changes in motor-evoked potential (MEP) amplitudes most likely represent synaptic plasticity and are thus termed LTP-like and LTD-like plasticity.

OBJECTIVE/HYPOTHESIS

We investigated the role of changes of motor threshold and their relation to changes of MEP amplitudes.

METHODS

We induced plasticity by paired associative stimulation (PAS) with 25 ms or 10 ms inter-stimulus interval or by motor practice (MP) in 64 healthy subjects aged 18-31 years (median 24.0).

RESULTS

We observed changes of MEP amplitudes and motor threshold after PAS[25], PAS[10] and MP. In all three protocols, long-term individual changes in MEP amplitude were inversely correlated to changes in motor threshold (PAS[25]: P = .003, n = 36; PAS[10]: P = .038, n = 19; MP: P = .041, n = 19).

CONCLUSION

We conclude that changes of MEP amplitudes and MT represent two indices of motor cortex plasticity. Whereas increases and decreases in MEP amplitude are assumed to represent LTP-like or LTD-like synaptic plasticity of motor cortex output neurons, changes of MT may be considered as a correlate of intrinsic plasticity.

A theory of rate coding control by intrinsic plasticity effects

Intrinsic plasticity (IP) is a ubiquitous activity-dependent process regulating neuronal excitability and a cellular correlate of behavioral learning and neuronal homeostasis. Because IP is induced rapidly and maintained long-term, it likely represents a major determinant of adaptive collective neuronal dynamics. However, assessing the exact impact of IP has remained elusive. Indeed, it is extremely difficult disentangling the complex non-linear interaction between IP effects, by which conductance changes alter neuronal activity, and IP rules, whereby activity modifies conductance via signaling pathways. Moreover, the two major IP effects on firing rate, threshold and gain modulation, remain unknown in their very mechanisms. Here, using extensive simulations and sensitivity analysis of Hodgkin-Huxley models, we show that threshold and gain modulation are accounted for by maximal conductance plasticity of conductance that situate in two separate domains of the parameter space corresponding to sub- and supra-threshold conductance (i.e. activating below or above the spike onset threshold potential). Analyzing equivalent integrate-and-fire models, we provide formal expressions of sensitivities relating to conductance parameters, unraveling unprecedented mechanisms governing IP effects. Our results generalize to the IP of other conductance parameters and allow strong inference for calcium-gated conductance, yielding a general picture that accounts for a large repertoire of experimental observations. The expressions we provide can be combined with IP rules in rate or spiking models, offering a general framework to systematically assess the computational consequences of IP of pharmacologically identified conductance with both fine grain description and mathematical tractability. We provide an example of such IP loop model addressing the important issue of the homeostatic regulation of spontaneous discharge. Because we do not formulate any assumptions on modification rules, the present theory is also relevant to other neural processes involving excitability changes, such as neuromodulation, development, aging and neural disorders.

Over the past decades, experimental and theoretical studies of the cellular basis of learning and memory have mainly focused on synaptic plasticity, the experience-dependent modification of synapses. However, behavioral learning has also been correlated with experience-dependent changes of non-synaptic voltage-dependent ion channels. This intrinsic plasticity changes the neuron's propensity to fire action potentials in response to synaptic inputs. Thus a fundamental problem is to relate changes of the neuron input-output function with voltage-gated conductance modifications. Using a sensitivity analysis in biophysically realistic models, we depict a generic dichotomy between two classes of voltage-dependent ion channels. These two classes modify the threshold and the slope of the neuron input-output relation, allowing neurons to regulate the range of inputs they respond to and the gain of that response, respectively. We further provide analytical descriptions that enlighten the dynamical mechanisms underlying these effects and propose a concise and realistic framework for assessing the computational impact of intrinsic plasticity in neuron network models. Our results account for a large repertoire of empirical observations and may enlighten functional changes that characterize development, aging and several neural diseases, which also involve changes in voltage-dependent ion channels.

Increased occlusal vertical dimension induces cortical plasticity in the rat face primary motor cortex

Previous studies have demonstrated that functional plasticity in the primary motor cortex (M1) is related to motor-skill learning and changes in the environment. Increased occlusal vertical dimension (iOVD) may modulate mastication, such as in the masticatory cycle, and the firing properties of jaw-muscle spindles. However, little is known about the changes in motor representation within the face primary motor cortex (face-M1) after iOVD. The purpose of the present study was to determine the effect of iOVD on the face-M1 using intracortical microstimulation (ICMS). In an iOVD group, the maxillary molars were built-up by 2mm with acrylic. The electromyographic (EMG) activities from the left (LAD) and right (RAD) anterior digastric (AD), masseter and genioglossus (GG) muscles elicited by ICMS within the right face-M1 were recorded 1, 2 and 8 weeks after iOVD. IOVD was associated with a significant increase in the number of sites within the face-M1 from which ICMS evoked LAD and/or GG EMG activities, as well as a lateral shift in the center of gravity of the RAD and LAD muscles at 1 and 2 weeks, but not at 8 weeks. These findings suggest that a time-dependent neuroplastic change within the rat face-M1 occurs in association with iOVD. This may be related to the animal's ability to adapt to a change in the oral environment.

Shift in the intrinsic excitability of medial prefrontal cortex neurons following training in impulse control and cued-responding tasks

Impulse control is an executive process that allows animals to inhibit their actions until an appropriate time. Previously, we reported that learning a simple response inhibition task increases AMPA currents at excitatory synapses in the prelimbic region of the medial prefrontal cortex (mPFC). Here, we examined whether modifications to intrinsic excitability occurred alongside the synaptic changes. To that end, we trained rats to obtain a food reward in a response inhibition task by withhold responding on a lever until they were signaled to respond. We then measured excitability, using whole-cell patch clamp recordings in brain slices, by quantifying action potentials generated by the injection of depolarizing current steps. Training in this task depressed the excitability of layer V pyramidal neurons of the prelimbic, but not infralimbic, region of the mPFC relative to behavioral controls. This decrease in maximum spiking frequency was significantly correlated with performance on the final session of the task. This change in intrinsic excitability may represent a homeostatic mechanism counterbalancing increased excitatory synaptic inputs onto those neurons in trained rats. Interestingly, subjects trained with a cue that predicted imminent reward availability had increased excitability in infralimbic, but not the prelimbic, pyramidal neurons. This dissociation suggests that both prelimbic and infralimbic neurons are involved in directing action, but specialized for different types of information, inhibitory or anticipatory, respectively.

Intrinsic neuronal excitability: implications for health and disease

The output of a single neuron depends on both synaptic connectivity and intrinsic membrane properties. Changes in both synaptic and intrinsic membrane properties have been observed during homeostatic processes (e.g., vestibular compensation) as well as in several central nervous system (CNS) disorders. Although changes in synaptic properties have been extensively studied, particularly with regard to learning and memory, the contribution of intrinsic membrane properties to either physiological or pathological processes is much less clear. Recent research, however, has shown that alterations in the number, location or properties of voltage- and ligand-gated ion channels can underlie both normal and abnormal physiology, and that these changes arise via a diverse suite of molecular substrates. The literature reviewed here shows that changes in intrinsic neuronal excitability (presumably in concert with synaptic plasticity) can fundamentally modify the output of neurons, and that these modifications can subserve both homeostatic mechanisms and the pathogenesis of CNS disorders including epilepsy, migraine, and chronic pain.

Anatomical and sensory experiential determinants of synaptic plasticity in layer 2/3 pyramidal neurons of mouse barrel cortex

A minority of layer 2/3 (L2/3) pyramidal neurons exhibit spike-timing-dependent long-term potentiation (LTP) in normally reared adolescent mice. To determine whether particular subtypes of L2/3 neurons have a greater capacity for LTP than others, we correlated the morphological and electrophysiological properties of L2/3 neurons with their ability to undergo LTP by using a spike-timing-dependent protocol applied via layer 4 inputs from the neighboring barrel column. No correlation was found between the incidence of LTP and the cell's electrophysiological properties, nor with their laminar or columnar location. However, in cortex of normal, undeprived mice, neurons that exhibited LTP had dendrites that extended farther horizontally than those that showed no plasticity, and this horizontal spread was due to off-axis apical dendrites. From a sample of reconstructed neurons, two-thirds of neurons' dendritic arborizations reached into at least one adjacent barrel column. We also tested whether this relationship persisted following a short period of whisker deprivation. The probability of inducing LTP increased from 33% in cortex of undeprived mice to 53% following 7 days of whisker deprivation, and the incidence of LTD with the same protocol decreased from 49% to 9%. In deprived cortex, neurons exhibiting LTP did not extend any farther horizontally than those that showed no plasticity. Whisker deprivation did not affect horizontal spread of dendrites nor dendritic structure in general but did produced an increase in spine density, both on basal and on apical dendrites, suggesting a possible substrate for the increased levels of LTP observed in deprived cortex.

Population diversity and function of hyperpolarization-activated current in olfactory bulb mitral cells

Although neurons are known to exhibit a broad array of intrinsic properties that impact critically on the computations they perform, very few studies have quantified such biophysical diversity and its functional consequences. Using in vivo and in vitro whole-cell recordings here we show that mitral cells are extremely heterogeneous in their expression of a rebound depolarization (sag) at hyperpolarized potentials that is mediated by a ZD7288-sensitive current with properties typical of hyperpolarization-activated cyclic nucleotide gated (HCN) channels. The variability in sag expression reflects a functionally diverse population of mitral cells. For example, those cells with large amplitude sag exhibit more membrane noise, a lower rheobase and fire action potentials more regularly than cells where sag is absent. Thus, cell-to-cell variability in sag potential amplitude reflects diversity in the integrative properties of mitral cells that ensures a broad dynamic range for odor representation across these principal neurons.

Neuronal activity causes rapid changes of lateral amygdala neuronal membrane properties and reduction of synaptic integration and synaptic plasticity in vivo

Neuronal membrane properties dictate neuronal responsiveness. Plasticity of membrane properties alters neuronal function and can arise in response to robust neuronal activity. Despite the potential for great impact, there is little evidence for a rapid effect of activity-dependent changes of membrane properties on many neuronal functions in vivo in mammalian brain. In this study it was tested whether periods of neuronal firing lead to a rapid change of membrane properties in neurons of a rat brain region important for some forms of learning, the lateral nucleus of the amygdala, using in vivo intracellular recordings. Our results demonstrate that rapid plasticity of membrane properties occurs in vivo, in response to action potential firing. This plasticity of membrane properties leads to changes of synaptic integration and subsequent synaptic plasticity. These changes require Ca(2+) and hyperpolarization-activated ion channels, but are NMDA independent. Furthermore, the parameters and time course of these changes would not have been predicted from most in vitro studies. The plasticity of membrane properties demonstrated here may represent a basic form of in vivo short-term plasticity that modifies neuronal function.

Short-term sleep deprivation increases intrinsic excitability of prefrontal cortical neurons

Short-term sleep deprivation (SD) has been shown to enhance cortical activity. However, alterations in the cellular excitability of cortical neurons following SD are not yet fully understood. The present study investigated the effects of 4-hour SD on pyramidal neurons in the prefrontal cortex (PFC) of rats using whole-cell patch-clamp recording. SD led to an increase in the initial slope of firing frequency-current curve and a decrease in frequency adaptation, which were reversed by recovery sleep (RS). Correspondingly, the total afterhyperpolarization (AHP) was reduced in the SD group and returned in the RS group. Furthermore, the component of AHP changed after SD seemed to be sensitive to Ca(2+). These observations indicate an enhancement in intrinsic excitability due to short-term SD, and suggest a role for Ca(2+)-dependent AHP in this change. The findings of the present study may provide a possible explanation for the SD-induced increase in cortical activity.

Spike-timing dependent plasticity beyond synapse - pre- and post-synaptic plasticity of intrinsic neuronal excitability

Long-lasting plasticity of synaptic transmission is classically thought to be the cellular substrate for information storage in the brain. Recent data indicate however that it is not the whole story and persistent changes in the intrinsic neuronal excitability have been shown to occur in parallel to the induction of long-term synaptic modifications. This form of plasticity depends on the regulation of voltage-gated ion channels. Here we review the experimental evidence for plasticity of neuronal excitability induced at pre- or postsynaptic sites when long-term plasticity of synaptic transmission is induced with Spike-Timing Dependent Plasticity (STDP) protocols. We describe the induction and expression mechanisms of the induced changes in excitability. Finally, the functional synergy between synaptic and non-synaptic plasticity and their spatial extent are discussed.

Activity-dependent changes in the electrophysiological properties of regular spiking neurons in the sensorimotor cortex of the rat in vitro

Sensorimotor performance is highly dependent on the level of physical activity. For instance, a period of disuse induces an impairment of motor performance, which is the result of combined muscular, spinal and supraspinal mechanisms. Concerning this latter origin, our hypothesis was that intrinsic properties and input/output coupling of cells within the sensorimotor cortex might participate to the alteration in cortical motor control. The aim of the present study was thus to examine the basic electrophysiological characteristics of cortical cells in control rats and in animals submitted to 14 days of hindlimb unloading, a model of sensorimotor deprivation. Intracellular recordings were obtained in vitro from coronal slices from cortical hindpaw representation area. We have also made an attempt to determine the morphological characteristics as well as the location of the investigated neurons by biocytin labelling. Passive properties of neurons were affected by hindlimb unloading: input resistance and time constant were decreased (-20%), the rheobase was increased (+34%), whereas the resting potential was unchanged. The frequency-current relationships were also modified, the curve being shifted towards right. The size of body area of recorded neurons was unchanged in unloaded rats. Taken together, these data reflect a decrease in excitability of cortical cells in response to a decreased cortical activation.